Smoking is the leading preventable cause of death in humans. Smoking increases the risk of many diseases, including various cancers (Bilano et al., 2015; Jacobs et al., 2015) and cardiovascular diseases (Lubin et al., 2016). Compared with non-smokers, smokers have a 2–4-fold increased risk of coronary heart disease and stroke as well as an increased risk of atrial fibrillation (Benowitz and Burbank, 2016). Despite public awareness of the dangers of smoking, smoking rates are increasing in many developing countries (Samet and Wipfli, 2010). Smoking affects the tissues, organs and gut microbiotas in humans (Ambrose and Barua, 2004; Sasco et al., 2004; Capurso and Lahner, 2017; Huang and Shi, 2019) and alters the environment in which the gut microbes live, thereby affecting the composition and function of the gut microbiota. Cigarette smoke contains many toxic substances and may affect the microbiota by promoting cytokine production in cells, mucin production (Allais et al., 2016), changes in oxygen tension (Jensen et al., 1991), and production of reactive oxygen species in the blood (Talukder et al., 2011). It may also affect the intestinal microbiome by increasing the intestinal pH (Tomoda et al., 2011), delaying gastric emptying (Miller et al., 1989) and reducing pancreatic bicarbonate secretion (Ainsworth et al., 1993).

Previous studies have focused on the effects of smoking on the gut microbiota. One study (Lee et al., 2018; Sublette et al., 2020) showed that smokers’ gut microbiome compositions differed significantly from those of never-smokers. In those who quit smoking, the microbiome returned to a similar composition as that of never-smokers. However, another study (Shanahan et al., 2018) found significantly less diversity in the small intestinal mucosal flora of people who quit smoking than in never-smokers, implying that quitting smoking also affects microbial diversity. One study (Wang et al., 2012) showed that mice exposed to side-stream smoking exhibited significant alterations in their gut microbes, including an increased abundance of Clostridium and decreased Firmicutes (Lactococcus and Ruminococcus), Enterobacteriaceae and segmented filamentous bacteria as well as changes in intestinal inflammatory levels.

Because few studies have explored the influence of smoking on the gut microbiota, and most recent studies used 16S rRNA gene sequencing, the results remained at the genus level (Lee et al., 2018; Sublette et al., 2020). Here, we, for the first time, used whole-genome sequencing (WGS) to explore the effects of smoking on the gut microbiota at the species level.

This study was conducted to initially explore the effects of smoking on the gut microbiota and understand how smoking affects the body. We, for the first time, used WGS to detect the effects of smoking on the gut microbiota. We found that smoking significantly affected the gut microbiota, and the α- and β-diversities differed significantly. At the species level, compared with those of non-smokers, the relative abundances of Bacteroidales bacterium pH8, eggerthii, faecis, gallinarum, massiliensis, salyersiae, stercoris, vulgatus and xylanisolvens; Lachnospira bacterium1157FAA, bacterium2146FAA, bacterium3146FAA, bacterium3157FAACT1, bacterium8157FAA and bacterium9143BFAA; and Ruminococcus albus, bromii, callidus, gnavus, lactaris, obeum and sp5139BFAA increased, while the relative abundances of Alistipes finegoldii, indistinctus, onderdonkii, putredinis, senegalensis, shahii and spAP11; Bacteroides caccae, cellulosilyticus, clarus, intestinalis, nordii, oleiciplenus, plebeius and uniformis; Eubacterium eligens, ramulus, rectale and ventriosum; and Roseburia hominis, torques and inulinivorans decreased in the smokers. Interestingly, the gut microbes that were enriched in the smokers were positively correlated with inflammatory markers, and the gut microbes that were enriched in the non-smokers were protective factors and were negatively correlated with inflammatory markers ( Figure 5 ).

From the known effects of smoking, including immune system alterations (Sorensen et al., 2010; Mahassni and Alajlany, 2020), direct antibacterial activity (Pavia et al., 2000) and changes in oxygen tension (Jensen et al., 1991), we can propose many hypotheses related to our findings and to the observed changes in bacterial community compositions. For non-smokers, α- and β-diversities in the gut microbiota differed significantly from those of smokers. Microbiota diversity is generally associated with health (Requena et al., 2018), and changes in immune homeostasis and reduced diversity due to smoking may adversely affect the disease statuses of smokers relative to microbial-immune interactions; thus, further study of these interactions is warranted.

Eubacterium ramulus, E. rectale and E. ventriosum were enriched in the non-smokers and were the bacteria most negatively correlated with inflammatory markers and produced large amounts of short-chain fatty acids (SCFAs). E. ramulus, E. rectale and E. ventriosum digested polysaccharides to produce SCFAs (Barcenilla et al., 2000; Pryde et al., 2002; Macfarlane and Macfarlane, 2011), which play key protective roles against inflammation. E. eligens strongly promoted production of IL-10, an anti-inflammatory cytokine, in in vitro cell experiments (Chung et al., 2017). These findings are consistent with our finding that these species were negatively correlated with inflammatory indicators. The next most relevant bacterium was Adlercreutzia equolifaciens, which was enriched in the non-smokers; it converts ingested isoflavones, which are abundant in legumes and soya beans, into equol (Maruo et al., 2008). Equol has a high affinity for the estrogen receptor (Setchell et al., 2009) and may be a selective estrogen receptor modulator. A. equolifaciens is involved in metabolizing polyphenols and produced bioactive molecules involved in ameliorating metabolic disorders in obesity and diabetes (Clavel et al., 2014). Akkermansia muciniphila is also strongly correlated with inflammatory markers. A. muciniphila adheres to the mucosal layer, may have beneficial properties (Zhang et al., 2019), and increases intestinal endocannabinoids, which control inflammation (Plovier et al., 2017) and have potential anti-inflammatory properties (Derrien et al., 2017). Additionally, Amuc_1100 (Plovier et al., 2017), a protein isolated from A. muciniphila, interacts with Toll-like receptor 2 and helps improve the gut barrier. Alistipes finegoldii, indistinctus, onderdonkii, putredinis, senegalensis, shahii and spAP11 were enriched in non-smokers and are reported to reduce gut inflammation. This is consistent with our findings, in which these species were negatively correlated with inflammatory markers.

Bacteroides caccae, cellulosilyticus, clarus, intestinalis, nordii, oleiciplenus, plebeius and uniformis were enriched in non-smokers. B. caccae, B. intestinalis and B. uniformis significantly reduced the release of lipopolysaccharide-induced IL-8 from HT-29 cells (Hiippala et al., 2020). In fecal microbiota transplantation, increased B. plebeius was associated with disease in patients with colitis. Clostridium leptum increased regulatory T cells in the spleen (Li et al., 2012) and inhibited inflammatory cytokine production to decrease inflammation (He et al., 2020) in mice. Faecalibacterium prausnitzii secreted seven peptides belonging to the microbial anti-inflammatory molecule (MAM), which inhibited the NF-κB pathway in vitro. F. prausnitzii also protects against inflammation in the gut by producing butyrate, an SCFA (Sokol et al., 2008; Ganesan et al., 2018). Parabacteroides distasonis, goldsteinii, unclassified and xylaniphila were enriched in non-smokers and helped decrease inflammation. P. distasonis reduced the expressions of Toll-like receptor 4, IL-4 and TNF-α and increased IL-10 expression in the colon (Koh et al., 2020). P. distasonis inhibits TNF-α production via macrophages in vitro (Kverka et al., 2011). P. goldsteinii can reduce intestinal inflammation and inhibit lung inflammation, and lipopolysaccharides derived from P. goldsteinii are anti-inflammatory (Lai et al., 2021). Roseburia hominis and inulinivorans were enriched in non-smokers. These bacteria all produce butyrate and SCFAs, which break down polysaccharides and reduce inflammation (Chu et al., 2019; Ticinesi et al., 2020; Zheng et al., 2020).

Bacteroides vulgatus and B. xylanisolvens were enriched in the smokers and were the most positively correlated with inflammatory markers. B. vulgatus and B. xylanisolvens are considered to promote colitis (Dziarski et al., 2016). B. vulgatus and B. xylanisolvens are Gram-negative and trigger systemic inflammation, including increased IL-6 and THF-α and insulin resistance (Leite et al., 2017; Higuchi et al., 2018). B. vulgatus stimulates CD4 cells and secretes specific antigens to induce colitis (Hoentjen et al., 2007; Kathania et al., 2020). Lachnospira bacterium1157FAA, bacterium2146FAA, bacterium3146FAA, bacterium3157FAACT1, bacterium8157FAA and bacterium9143BFAA were enriched in the smokers and were positively correlated with inflammatory markers. One study found that a high-fat diet increased the abundance of Lachnospira and the inflammatory status in mice with colitis (Zeng et al., 2016). Prevotella stercorea was positively correlated with colonic dendritic cell activation levels in vivo and increased strong proinflammatory cytokine production. Consistent with our findings, Ruminococcus albus, bromii, callidus, gnavus, lactaris, obeum and sp5139BFAA promoted inflammation. R. gnavus can produce specific antigens and stimulate immune cells to produce corresponding antibodies, thus increasing inflammation (Hall et al., 2017; Bunker et al., 2019).

Although the metabolic pathways in the gut microbiotas differed between the groups, these differences were not functionally significant. In both groups, several pathways, whose functions included nucleoside synthesis, biosynthesis, degradation of carbohydrates, degradation of amino acids and nucleotides, and generation of precursor metabolites and energy, were individually enriched. Interestingly, nine distinct pathways that were enriched in smokers were responsible for amino acid biosynthesis, including L-serine, glycine, L-isoleucine, L-valine, L-methionine, L-lysine, L-threonine and aspartate. Our hypothesis is that accumulation of amino acids, the basic structures of proteins, may be due to the increased demand for amino acids caused by changes in the bacterial abundances due to smoking, thereby increasing the amino acid abundances.

The participants in our study came in for routine checkups and were thus more likely to represent the healthy population in China. We implemented a rigorous screening process and excluded those with systemic diseases, excessive alcohol consumption, drug use and enteric diseases, which was an advantage of this study. Our analysis included both smokers and non-smokers. However, participants were more likely to underestimate their smoking habits, resulting in their actual smoking status being unreported. Participants’ daily environments were also unknown (e.g., passive smoking) and may have influenced our results, which may have influenced our analysis. Therefore, these factors must be further analyzed to understand the impact of smoking on the gut microbiota.

Smoking alters bacterial communities in the stool, and this alteration may be associated with inflammation. Many studies have shown that the main characteristic of chronic diseases is systemic inflammation. Smoking increases inflammation in the body by causing accumulation of inflammation-promoting bacteria, such as Bacteroides, Lachnospira, Prevotella stercorea and Ruminococcus, in the gut. Conversely, the microbiotas of non-smokers were enriched with bacteria that inhibit inflammation, including Eubacterium, Adlercreutzia equolifaciens, Akkermansia muciniphila, Alistipes and Bacteroides. The mechanism of interaction between the gut microbiota and inflammation requires further study.

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ebi.ac.uk/ena, PRJEB36271.

The studies involving human participants were reviewed and approved by Ethics Review Committee of scientific Research Projects in the First Affiliated Hospital of Zhengzhou University. The patients/participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.

SY researched the data, performed the analysis and wrote and edited the manuscript. ZM and MJ helped to collect the data and edit the manuscript. AL is the guarantor of this work and as such had full access to all data in the study and takes responsibility of the integrity of the data and the accuracy of the data analysis. SD was in charge of the project. All authors contributed to the article and approved the submitted version.

This research was equally funded and supported by the Chinese National Science and Technology Major Project (2018ZX10305410), the Henan Province Medical Science and Technique Project grant (2018020001), the Henan Province Postdoctoral Research grant (001801005) and the Key Scientific Research Projects of Universities in Henan Province (21A320035).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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